Feature selection (FS) is considered to be a hard optimization problem in data mining and
some artificial intelligence fields. It is a process where rather than studying all of the features …

An inherent problem in software engineering is that competing prediction systems have
been found to produce conflicting results. Yet accurate prediction is crucial because the …

Feature selection (FS) is the process of finding the least possible number of features that are
able to describe a dataset in the same way as the original features. Feature selection is a …

Gene Selection (GS) is a strategy method targeted at reducing redundancy, limited
expressiveness, and low informativeness in gene expression datasets obtained by DNA …

Abstract In the Internet of Things (IoT), the data that are sent via devices are sometimes
unrelated, duplicated, or erroneous, which makes it difficult to perform the required tasks …

Scientific communities are still motivated to create novel approaches and methodologies for
early estimation of software project development efforts and testing efforts in soft computing …

Classification is used to categorize data and produce decisions for several domains. To
improve the accuracy of classification, researchers have tended to hybridize the neural …

Feature selection (FS) is used to solve hard optimization problems in artificial intelligence
and data mining. In the FS process, some, rather than all of the features of a dataset are …

In this paper, software effort prediction (SEP) and software test prediction (STP)(ie, software
reliability problems) are tackled by integrating the salp swarm algorithm (SSA) with a …

The vehicle routing problem (VRP) is one of the challenging problems in optimization and
can be described as combinatorial optimization and NP-hard problem. Researchers have …